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. 2020 Dec:191:110184.
doi: 10.1016/j.envres.2020.110184. Epub 2020 Sep 16.

How socio-economic and atmospheric variables impact COVID-19 and influenza outbreaks in tropical and subtropical regions of Brazil

Leila Droprinchinski Martins  1 , Iara da Silva  2 , Wellington Vinicius Batista  2 , Maria de Fátima Andrade  3 , Edmilson Dias de Freitas  3 , Jorge Alberto Martins  2
Affiliations

How socio-economic and atmospheric variables impact COVID-19 and influenza outbreaks in tropical and subtropical regions of Brazil

Leila Droprinchinski Martins et al. Environ Res. 2020 Dec.

Abstract

COVID-19 has been disturbing human society with an intensity never seen since the Influenza epidemic (Spanish flu). COVID-19 and Influenza are both respiratory viruses and, in this study, we explore the relations of COVID-19 and Influenza with atmospheric variables and socio-economic conditions for tropical and subtropical climates in Brazil. Atmospheric variables, mobility, socio-economic conditions and population information were analyzed using a generalized additive model for daily COVID-19 cases from March 1st to May 15th, 2020, and for daily Influenza hospitalizations (2017-2019) in Brazilian states representing tropical and subtropical climates. Our results indicate that temperature combined with humidity are risk factors for COVID-19 and Influenza in both climate regimes, and the minimum temperature was also a risk factor for subtropical climate. Social distancing is a risk factor for COVID-19 in all regions. For Influenza and COVID-19, the highest Relative Risks (RR) generally occurred in 3 days (lag = 3). Altogether among the studied regions, the most important risk factor is the Human Development Index (HDI), with a mean RR of 1.2492 (95% CI: 1.0926-1.6706) for COVID-19, followed by the elderly fraction for both diseases. The risk factor associated with socio-economic inequalities for Influenza is probably smoothed by Influenza vaccination, which is offered free of charge to the entire Brazilian population. Finally, the findings of this study call attention to the influence of socio-economic inequalities on human health.

Keywords: Climate; Respiratory diseases; SARS-CoV-2; Transmission diseases; Virus.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Geographical position of Brazilian states and meteorological stations.
Fig. 2
Fig. 2
Boxplot of atmospheric variables and mobility from March 1st to May 15th, 2020.
Fig. 3
Fig. 3
Prevalence of COVID-19 (number/100,000 inhabitants) cases (a) and deaths (b) for the Brazilian states.
Fig. 4
Fig. 4
Exposure-response curves of mobility (%) and Relative Risks (RR) for states at lag 3.
Fig. 5
Fig. 5
State prevalence of daily Influenza (number of hospitalization/100,000 inhabitants) for 2017–2019. In the left panel, box plots comparing prevalence among states. In the right, the average annual profile for each state.
Fig. 6
Fig. 6
Exposure-response curves of maximum temperature (°C) and relative humidity (%) and their RR at lag 3 for AM (tropical climate). a) and b) for COVID-19 cases and c) and d) for Influenza hospitalizations. Vertical lines mean the 25th, 75th, and 99th percentiles.
Fig. 7
Fig. 7
Exposure-response curves of maximum temperature (°C) and relative humidity (%) and their RR at lag 3 for PR (subtropical climate). a) and b) for COVID-19 cases and c) and d) for Influenza hospitalizations. Vertical lines mean the 25th, 75th, and 99th percentiles.
See this image and copyright information in PMC

References

    1. Alonso W.J., Viboud C., Simonsen L., Hirano E.W., Daufenbach L.Z., Miller M.A. Seasonality of influenza in Brazil: a traveling wave from the amazon to the subtropics. Am. J. Epidemiol. 2007;165:1434–1442. doi: 10.1093/aje/kwm012. - DOI - PubMed
    1. Alvares C.A., Stape J.L., Sentelhas P.C., De Moraes Gonçalves J.L., Sparovek G. Köppen’s climate classification map for Brazil. Meteorol. Z. 2013;22:711–728. doi: 10.1127/0941-2948/2013/0507. - DOI
    1. Aquino E.M.L., Silveira I.H., Pescarini J.M., Aquino R., Souza-Filho J.A. Social distancing measures to control the COVID-19 pandemic : potential impacts and challenges in Brazil 2423–2446. Ciência e Saúde Coletiva. 2020;25:2423–2446. doi: 10.1590/1413-81232020256.1.10502020. - DOI - PubMed
    1. Auler A.C., Cássaro F.A.M., da Silva V.O., Pires L.F. Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: a case study for the most affected Brazilian cities. Sci. Total Environ. 2020;729 doi: 10.1016/j.scitotenv.2020.139090. - DOI - PMC - PubMed
    1. Banerjee A., Pasea L., Harris S., Gonzalez-Izquierdo A., Torralbo A., Shallcross L., Noursadeghi M., Pillay D., Sebire N., Holmes C., Pagel C., Wong W.K., Langenberg C., Williams B., Denaxas S., Hemingway H. Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. Lancet. 2020;395:1715–1725. doi: 10.1016/s0140-6736(20)30854-0. - DOI - PMC - PubMed